Resumen
Introducción: en México existe escasa información respecto al vínculo entre el síndrome metabólico (MetS), el nivel socioeconómico (NSE) y la calidad de vida (CdV) de la población.
Objetivo: evaluar la asociación entre sujetos que tienen alto riesgo de desarrollar MetS con NSE y CdV.
Material y métodos: se invitó a participar a pacientes de la UMF-2 del IMSS y del Centro Urbano-SSA Clínica-1. Se recolectaron medidas antropométricas y se aplicaron los cuestionarios AMAI, SF12 y ESF-I para NSE, CdV y MetS, respectivamente. La asociación se determinó calculando rho de Spearman. El riesgo se evaluó mediante regresión logística (razon de momios e intervalo de confianza del 95%).
Resultados: la diferencia entre NSE (193 ± 53 frente a 124 ± 50) y CdV (86.3 ± 14.8 frente a 56.0 ± 25.4) fue significativa entre los grupos de bajo y alto riesgo, respectivamente (p < 0.001). Hubo una fuerte correlación negativa entre las puntuaciones de la ESF-I y NSE (rho = -0.623, p < 0.001) así como con la CdV (rho = -0.719, p < 0.001). El riesgo de MetS aumentó al disminuir el NSE (C+: OR = 6.4, IC95%: 3.2 - 13.0; D: OR = 66.1, IC95%: 23.2 - 188.3), mientras que el aumento de la CdV lo atenuó (OR = 0.93, IC95%: 0.91 - 0.94). Interesantemente, la CdV mitigó el efecto del NSE (C+: OR = 4.5, IC95%: 2.1 - 9.6; D: OR = 11.9, IC95%: 3.8 - 37.6).
Conclusión: Una menor CdV y NSE aumentan el riesgo de MetS en la región centro de México; sin embargo, el aumento en la CdV podría disminuir el efecto que tiene el NSE en el desarrollo de MetS.
Abstract
Background: In Mexico there is little information regarding the link between metabolic syndrome (MetS), socioeconomic status (SES) and quality of life (QoL)
Objective: To assess the association between subjects who are at high risk of developing MetS with SES and QoL.
Material and methods: Patients attending UMF-2 IMSS or Centro Urbano-SSA Clínica-1 were asked to participate. Anthropometric measures were collected, the AMAI, SF12, and ESF-I questionnaire where apply for SES, QoL, and MetS, respectively. Association were determined by calculating Spearman’s rho and the risk (odds ratio and 95% confidence-interval) was assessed using logistic regression.
Results: The difference of SES (193 ± 53 vs. 124 ± 50) and QoL (86.3 ± 14.8 vs. 56.0±25.4) questionnaires were significantly between low-risk and high-risk groups, respectively (p < 0.001). There was a negative correlation between ESF-I and SES (rho = -0.623, p < 0.001) as well as the QoL (rho = -0.719, p < 0.001). MetS risk was augmented by decreasing SES (C+: OR = 6.4, 95%IC: 3.2-13.0; D: OR = 66.1, 95%IC: 23.2-188.3), whereas increasing QoL attenuated it (OR = 0.93, 95%CI: 0.91-0.94). However, QoL mitigated the effect of SES (C+: OR = 4.5, 95%IC: 2.1-9.6; D: OR = 11.9, 95%IC: 3.8-37.6).
Conclusion: Lower QoL and SES increased the risk of MetS in Central Mexico; however, improving the QoL can mitigated the effect SES has on developing MetS.
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